---
title: "How to price an AI product: seats, usage or outcomes"
description: "How to price an AI product when inference costs grow with use: seats, usage, outcomes or hybrids, with margin math and real GitHub and Salesforce pricing."
image: https://roasexpert.com/hubfs/roas-expert-visuals/cover-pricing-an-ai-product.png
---

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 October 4, 2026

# Pricing an AI product: seats, usage or outcomes

![Picture of Rishabh Gupta](https://roasexpert.com/hs-fs/hubfs/IMG_1011.jpeg?width=50&name=IMG_1011.jpeg) [Rishabh Gupta](https://roasexpert.com/blog/author/rishabh-gupta)

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For most AI products, the right answer is a hybrid: a seat or platform fee that includes a set amount of usage, with a published overage rate after that. Use pure seats only when the AI assists a person and usage per person is fairly even. Use pure usage for technical buyers who can model their volume, and charge per outcome only when you can verify the result and it's mostly your doing.

The market is already moving this way. GitHub [moved Copilot to usage-based billing](https://github.blog/changelog/2026-06-01-updates-to-github-copilot-billing-and-plans/) with AI credits on June 1, 2026. Salesforce sells Agentforce per user, per conversation and per action. Intercom, Zendesk and HubSpot bill their AI support agents on outcomes such as resolved conversations. ICONIQ's [2026 State of AI report](https://www.iconiq.com/growth/reports/state-of-ai-2026), based on a Q2 2026 survey of about 300 executives at software companies building AI products, says consumption-based pricing rose from 35% to 42% in six months and outcome-based pricing from 18% to 23%. The average company blends 1.7 pricing models.

## Why per-seat pricing breaks for AI products

Classic SaaS could sell seats because serving one more user cost almost nothing. AI doesn't work that way. Bessemer's [AI pricing and monetization playbook](https://www.bvp.com/atlas/the-ai-pricing-and-monetization-playbook) (February 2026) points out that every AI query carries a real cost, and puts AI companies' gross margins at 50 to 60%, against 80 to 90% for SaaS. Three things go wrong under a flat seat price.

1. Cost per user varies. Your bill scales with actions, tokens and the model behind each request, not with headcount. When GitHub [announced its switch](https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing/), it wrote that "a quick chat question and a multi-hour autonomous coding session can cost the user the same amount," and called its premium request model "no longer sustainable."
2. Heavy users dominate cost. Explaining its own 2025 change, [Cursor wrote](https://cursor.com/blog/june-2025-pricing) that "the hardest requests cost an order of magnitude more than simple ones." Under a flat seat, your light users pay for your heavy ones.
3. Agents shrink the seat count. Say your agent closes a third of a customer's support tickets. At renewal they need fewer support seats, so your revenue falls as your product gets better. Some vendors now price people and agents separately. Salesforce prices employee-facing Agentforce at $125 a user a month with unmetered use, but bills customer-facing agents at $2 a conversation, according to its [pricing page](https://www.salesforce.com/agentforce/pricing/).

## Seats, usage, outcomes and hybrids compared

Here's how each model bills, with a public example checked on the vendor's own page in October 2026.

![Three ways to price an AI product: seats are simple to buy but margin drops with heavy users, usage tracks cost but is hard to forecast, outcomes are easy to justify but need clean attribution.](https://roasexpert.com/hubfs/roas-expert-visuals/ai-startups-pricing-models.svg)

Each model has one strength and one risk. Most AI products land on a hybrid.

| Model and public example | How it bills | When it fits | Main risk |
| --- | --- | --- | --- |
| Per seat: [Microsoft 365 Copilot](https://www.microsoft.com/en-us/microsoft-365/copilot/enterprise) | $30 a user a month, paid yearly | AI assists a person and use per person is even | Heavy users erase margin, and agents shrink seat counts |
| Seats with usage limits: [GitHub Copilot Business](https://docs.github.com/en/copilot/get-started/plans) | $19 a user a month including 1,900 AI credits, then $0.01 a credit | Use varies widely between people on the same team | Users hit limits mid-task |
| Usage: [Salesforce Flex Credits](https://www.salesforce.com/agentforce/pricing/) | $500 per 100,000 credits, with 20 credits ($0.10) per action | Technical buyers, APIs and background agents | Bills are hard to forecast, so buyers ration use |
| Fee with included usage and overage: [Cursor](https://cursor.com/docs/account/pricing) | $20 a month with a set amount of model usage, then on-demand usage at API rates | A mix of light and heavy users | Bill shock if users can't see the meter |
| Outcome: [Intercom Fin](https://fin.ai/pricing) | $0.99 per outcome, charged at most once per conversation | Results you can verify and mostly control | Disputes over what counts, and you pay for failed attempts |

Microsoft shows a clean split between people and agents. [Microsoft 365 Copilot](https://www.microsoft.com/en-us/microsoft-365/copilot/enterprise) is a $30 seat, but agent use in Copilot Chat can be [billed pay-as-you-go at $0.01 per message](https://learn.microsoft.com/en-us/microsoft-365/copilot/pay-as-you-go/meters) to an Azure subscription. Seats for people, meters for agents is a pattern worth copying.

[GitHub's plans](https://docs.github.com/en/copilot/get-started/plans) and [Cursor's plans](https://cursor.com/docs/account/pricing) show the hybrid I'd start most AI apps on: a subscription that includes usage, with pay-as-you-go after it. Salesforce's [Flex Credits](https://www.salesforce.com/news/press-releases/2025/05/15/agentforce-flexible-pricing-news/), announced in May 2025, meter each agent action. On outcomes, Intercom's [Fin](https://fin.ai/pricing) charges per outcome, and HubSpot [moved its Customer Agent](https://www.hubspot.com/company-news/hubspots-customer-agent-and-prospecting-agent-now-you-pay-when-the-task-is-complete) from $1.00 per conversation to $0.50 per resolved conversation on April 14, 2026. Notice that HubSpot bills that outcome in credits. Outcome as the trigger and credits as the currency is a hybrid too.

## Gross margin math: an illustration

Gross margin per user is price minus inference cost, divided by price. Inference cost is actions times your cost per action. Run it across your real usage spread, not for the average user.

Here's an illustration with made-up numbers. Say you sell an AI assistant at $40 a seat a month, and each action, such as a research task or a drafted email, costs you $0.05 in inference.

| User | Actions a month | Inference cost | Gross margin |
| --- | --- | --- | --- |
| Light | 100 | $5 | 87.5% |
| Typical | 300 | $15 | 62.5% |
| Heavy | 1,200 | $60 | -50% |

Past 800 actions a month, a seat loses money. Now spread 100 seats as 50 light, 40 typical and 10 heavy. Revenue is $4,000, inference is $1,450 and blended margin is 63.75%. That looks fine until you see that the heavy 10% of seats drive 41% of inference cost. Your margin now depends on who signs up next.

Add a limit. Keep the $40 seat, include 500 actions and charge $0.10 for each action after that. Light and typical users never notice. The heavy user pays $110 against $60 of cost, a 45% margin instead of minus 50%, and blended margin rises to about 69%.

Then stress test the model. If you switch to a model that doubles your cost per action to $0.10, the typical flat-seat user falls to a 25% margin and the heavy one costs you $120 against $40 of revenue. GitHub now [converts tokens into credits](https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing/) at each model's published API rate, so its meter tracks model cost. Your meter should move when your costs do.

Outcome pricing changes the denominator. You pay inference on every attempt but bill only the wins. At $1.00 per resolution and $0.15 of inference per conversation, a 60% resolution rate means $0.25 of cost per billed resolution, a 75% margin. At a 30% resolution rate, cost per billed resolution doubles to $0.50 and margin drops to 50%. A customer with a thin help center can double your cost per resolution.

This is the same discipline we apply to paid media: judge spend on profit, not revenue. If you buy growth with ads, the payback math in [ROAS, MER and POAS](https://roasexpert.com/blog/roas-mer-poas) depends on this margin.

## How do you choose a value metric?

The value metric is the unit your price scales with. A good one passes four tests.

1. It moves with customer value. When customers get more from the product, they use more of the metric.
2. The buyer can predict it. Their finance team can forecast next quarter's bill without calling you.
3. Both sides can measure it. The customer sees the same count you bill from, as it happens.
4. It covers your cost. When your inference bill rises, so does the metric.

Seats pass tests 2 and 3, then fail test 4 once usage spreads out. Tokens pass 3 and 4, fail 1, and fail 2 for any buyer who isn't an engineer. Credits are tokens with a friendlier label, so they pass test 2 only when you pair them with included pools and caps. Resolutions pass test 1, pass test 3 only if you publish the definition, and pass test 4 only if your price covers failed attempts.

Published definitions differ, so read them closely. Intercom [counts a Fin resolution](https://fin.ai/help/en/articles/13975800-fin-pricing-outcomes) when the customer confirms it, or when the customer goes quiet for 24 hours after Fin's last answer. It doesn't bill when the customer asks for a human. Zendesk [announced outcome-based pricing](https://www.zendesk.com/newsroom/articles/zendesk-outcome-based-pricing/) in August 2024. Since May 18, 2026, only [verified resolutions](https://support.zendesk.com/hc/en-us/articles/9570369117338-About-automated-resolution-tiers) count against its allowance, and an LLM reviews each conversation to confirm the request was resolved. Pick a definition, write it down and show it on every invoice.

## Packaging moves that protect margin

1. Included usage. Size it to your typical user, not your average one, because heavy users pull the average up. GitHub Copilot Business includes 1,900 AI credits per user and [pools them](https://docs.github.com/copilot/concepts/billing/usage-based-billing-for-organizations-and-enterprises), so 100 users share 190,000 credits. Pooling is friendlier to buyers, but your margin then lives at the account level. In the illustration above, a pooled 50,000-action allowance would cover all 29,000 actions, and overage would never bill.
2. Rollover. [GitHub](https://docs.github.com/copilot/concepts/billing/usage-based-billing-for-organizations-and-enterprises) and [HubSpot](https://www.hubspot.com/products/artificial-intelligence/credits) both expire unused included credits at the end of each month. That stops unused credits piling up into a usage spike later. If you allow rollover, cap it at one month's allowance.
3. Overage rates. Publish them. GitHub [charges $0.01](https://docs.github.com/en/copilot/get-started/plans) per extra AI credit. [Zendesk](https://www.zendesk.com/pricing/) charges $1.50 per extra automated resolution on a commitment and $2.00 pay-as-you-go. HubSpot's [default](https://knowledge.hubspot.com/account-management/understand-hubspot-credits-and-billing), once you've bought extra credits and hit your monthly limit, is to move you to a larger credit pack for the rest of your term. Per-credit overage is a setting you turn on.
4. Spend caps and alerts. GitHub's user-level [budgets](https://docs.github.com/en/copilot/concepts/billing-and-usage/organizations-and-enterprises/budgets) are a hard stop, while its organization and enterprise budgets stop usage only if an admin turns that setting on. HubSpot [alerts admins](https://knowledge.hubspot.com/account-management/understand-hubspot-credits-and-billing) at 75%, 85% and 90% of credits used. Turn caps on by default for new accounts, and send the first alert early enough for the buyer to act.
5. Annual commits. Trade a lower unit rate for committed volume. Salesforce sells Flex Credits [pay-as-you-go or pre-purchased](https://www.salesforce.com/news/stories/new-agentforce-payment-options/), and says pre-purchase gets the best overall rate. Commits give you forecastable revenue and give the buyer a number to budget.

## How do you change pricing without losing trust?

Cursor shows the cost of getting this wrong. On June 16, 2025 it replaced the Pro plan's 500 monthly requests with "$20 of frontier model usage per month at API pricing." [TechCrunch reported](https://techcrunch.com/2025/07/07/cursor-apologizes-for-unclear-pricing-changes-that-upset-users/) users running out of usage quickly and getting unexpected charges. On July 4, Cursor CEO Michael Truell [wrote](https://cursor.com/blog/june-2025-pricing) that the changes "were not communicated clearly, and we take full responsibility." Cursor offered refunds for unexpected usage between June 16 and July 4, improved its pricing page and docs, and added usage-limit visibility to its dashboard.

GitHub's 2026 switch shows the other way. It [announced usage-based billing](https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing/) on April 27, five weeks before the June 1 start. Annual Pro and Pro+ subscribers kept premium request pricing until their plans expire. Business and Enterprise customers got larger promotional credit allowances for June, July and August. GitHub promised a preview bill for early May and, on May 12, published [downloadable reports](https://github.blog/changelog/2026-05-12-april-reports-are-now-available-to-prepare-for-usage-based-billing/) showing how each customer's April activity would translate into credits.

The rules that follow:

1. Give notice measured in billing cycles, and more for annual contracts.
2. Grandfather existing contracts until renewal.
3. Show each customer their own bill under the new price before it applies, and give new buyers a calculator.
4. Refund surprises fast, and say plainly what you got wrong.

## How to test pricing before you set limits

1. Instrument cost per account first. Log actions, tokens, model and cost for every user from the first beta. You can't price a distribution you haven't measured.
2. Read the distribution, not the average. Look at the median, the 90th percentile and the top 1% of users by actions and by cost. Set included usage so the typical user never sees a limit, and price overage for the tail.
3. Interview the buyer, not just the user. Ask what the job costs them today in people, tools or agencies, whether they budget for it as a fixed annual line or a variable one, who approves overage, and which result they'd pay for per unit.
4. Measure willingness to pay. Van Westendorp's price sensitivity meter asks four questions: at what price the product is so cheap you'd doubt its quality, a bargain, getting expensive, and too expensive to consider. It gives you a range of acceptable prices, not a single number. [Sawtooth Software](https://sawtoothsoftware.com/resources/blog/posts/van-westendorp-pricing-sensitivity-meter) notes it suits products new to the market and leaves out competitors, so pair it with your interviews and add a purchase-intent question.
5. Pilot on new customers. Launch the new package to new signups first, then watch overage, upgrades and churn by cohort for two or three billing cycles before you move existing customers.

## If you want help

Pricing is part of our [product consulting](https://roasexpert.com/product-consulting) work with [AI startups](https://roasexpert.com/ai-startups) and SaaS teams. A product and GTM teardown costs $2,000, and a fractional product lead starts at $3,000 a month for one day a week. [Book a 30-minute call](https://roasexpert.com/contact) to talk it through.

## Sources

- [State of AI: The Builder's Economy (2026), ICONIQ](https://www.iconiq.com/growth/reports/state-of-ai-2026)
- [The AI pricing and monetization playbook, Bessemer Venture Partners](https://www.bvp.com/atlas/the-ai-pricing-and-monetization-playbook)
- [GitHub Copilot is moving to usage-based billing, The GitHub Blog](https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing/)
- [Updates to GitHub Copilot billing and plans, GitHub Changelog](https://github.blog/changelog/2026-06-01-updates-to-github-copilot-billing-and-plans/)
- [Plans for GitHub Copilot, GitHub Docs](https://docs.github.com/en/copilot/get-started/plans)
- [Usage-based billing for organizations and enterprises, GitHub Docs](https://docs.github.com/copilot/concepts/billing/usage-based-billing-for-organizations-and-enterprises)
- [Budgets for usage-based billing, GitHub Docs](https://docs.github.com/en/copilot/concepts/billing-and-usage/organizations-and-enterprises/budgets)
- [April reports are now available to prepare for usage-based billing, GitHub Changelog](https://github.blog/changelog/2026-05-12-april-reports-are-now-available-to-prepare-for-usage-based-billing/)
- [Clarifying our pricing, Cursor](https://cursor.com/blog/june-2025-pricing)
- [Pricing, Cursor Docs](https://cursor.com/docs/account/pricing)
- [Cursor apologizes for unclear pricing changes that upset users, TechCrunch](https://techcrunch.com/2025/07/07/cursor-apologizes-for-unclear-pricing-changes-that-upset-users/)
- [Agentforce pricing, Salesforce](https://www.salesforce.com/agentforce/pricing/)
- [Salesforce Introduces New Flexible Agentforce Pricing to Accelerate the Digital Labor Revolution, Salesforce](https://www.salesforce.com/news/press-releases/2025/05/15/agentforce-flexible-pricing-news/)
- [New Ways to Pay Make It Easier than Ever to Get Started with Agentforce, Salesforce](https://www.salesforce.com/news/stories/new-agentforce-payment-options/)
- [Microsoft 365 Copilot for enterprise, Microsoft](https://www.microsoft.com/en-us/microsoft-365/copilot/enterprise)
- [Meters for Microsoft Copilot pay-as-you-go services, Microsoft Learn](https://learn.microsoft.com/en-us/microsoft-365/copilot/pay-as-you-go/meters)
- [Fin AI Agent pricing, Intercom](https://fin.ai/pricing)
- [Fin pricing: Outcomes, Fin Help Center](https://fin.ai/help/en/articles/13975800-fin-pricing-outcomes)
- [Zendesk First in CX Industry to offer Outcome-Based Pricing for AI Agents, Zendesk](https://www.zendesk.com/newsroom/articles/zendesk-outcome-based-pricing/)
- [Zendesk pricing plans, Zendesk](https://www.zendesk.com/pricing/)
- [About automated resolution tiers, Zendesk Help](https://support.zendesk.com/hc/en-us/articles/9570369117338-About-automated-resolution-tiers)
- [HubSpot's Customer Agent and Prospecting Agent: Now you pay when the task is complete, HubSpot](https://www.hubspot.com/company-news/hubspots-customer-agent-and-prospecting-agent-now-you-pay-when-the-task-is-complete)
- [HubSpot Credits, HubSpot](https://www.hubspot.com/products/artificial-intelligence/credits)
- [Manage HubSpot Credits, HubSpot Knowledge Base](https://knowledge.hubspot.com/account-management/understand-hubspot-credits-and-billing)
- [Van Westendorp Pricing Model: Definition, How It Works, Examples, and More, Sawtooth Software](https://sawtoothsoftware.com/resources/blog/posts/van-westendorp-pricing-sensitivity-meter)

Facts checked on 4 October 2026.

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  "name" : "ROAS Expert",
  "publisher" : {
    "@id" : "https://roasexpert.com/#org"
  },
  "url" : "https://roasexpert.com/"
}
```

```json
{
  "@context" : "https://schema.org",
  "@id" : "https://roasexpert.com/#rishabh",
  "@type" : "Person",
  "jobTitle" : "Founder",
  "name" : "Rishabh Gupta",
  "sameAs" : [ "https://www.linkedin.com/in/rishabh16/" ],
  "worksFor" : {
    "@id" : "https://roasexpert.com/#org"
  }
}
```